Image-forming MR methods which utilize the interaction between magnetic field and nuclear spins in order to form two-dimensional or three-dimensional images are widely used nowadays, notably in the field of medical diagnostics, because for the imaging of soft tissue they are superior to other imaging methods in many respects, they do not require ionizing radiation, and they are usually not invasive.
According to the MR method in general, the body of a patient or in general an object to be examined is arranged in a strong, uniform magnetic field B0 whose direction at the same time defines an axis, normally the z-axis, of the coordinate system on which the measurement is based.
The magnetic field produces different energy levels for the individual nuclear spins in dependence on the applied magnetic field strength. These spins can be excited (spin resonance) by application of an alternating electromagnetic field (RF field) of defined frequency, the so called Larmor frequency or MR frequency. From a macroscopic point of view the distribution of the individual nuclear spins produces an overall magnetization which can be deflected out of the state of equilibrium by application of an electromagnetic pulse of appropriate frequency (RF pulse) while the magnetic field extends perpendicularly to the z-axis, so that the magnetization performs a precessional motion about the z-axis.
Any variation of the magnetization can be detected by means of receiving RF antennas, which are arranged and oriented within an examination volume of the MR device in such a manner that the variation of the magnetization is measured in a direction perpendicular to the z-axis.
In order to realize spatial resolution in the body, constant magnetic field gradients extending along the three main axes are superposed on the uniform magnetic field, leading to a linear spatial dependency of the spin resonance frequency. The signal picked up in the receiving antennas then contains components of different frequencies which can be associated with different locations in the body.
The signal data obtained via the receiving antennas correspond to the spatial frequency domain and are called k-space data. The k-space data usually include multiple lines acquired with different phase encoding. Each line is digitized by collecting a number of samples. A set of samples of k-space data is converted to an MR image, e.g. by means of Fourier transformation.
In MRI, it is often desired to obtain information about the relative contribution of two dominant chemical species, such as water and fat, to the overall signal, either to suppress the contribution of one of them or to separately or jointly analyze the contribution of both of them. These contributions can be calculated if information from two or more corresponding echoes, acquired at different echo times, is combined.
A way to obtain information on water and fat contributions to the MR signal at the same time is chemical shift encoding, in which an additional dimension, the chemical shift dimension, is defined and encoded by acquiring a couple of images at slightly different echo times.
In particular for water-fat separation, these types of experiments are often called Dixon-type of measurements. By means of Dixon imaging or Dixon water/fat imaging, a water-fat separation can be obtained by calculating contributions of water and fat from two or more corresponding echoes, acquired at different echo times. Dixon imaging usually relies on the acquisition of at least two echoes to separate water and fat signals. In general these kinds of separations are possible because there is a known precessional frequency difference of hydrogen in fat and water. In its simplest form, water and fat images are generated by either addition or subtraction of the ‘in phase’ and ‘out of phase’ datasets, but this approach is rather sensitive to main field inhomogeneities.
High quality water-fat separation with no residual fat signal in water images may be obtained in case complex models of the fat spectrum are incorporated into the water-fat separation process. This has for example been demonstrated for three-point Dixon methods in Yu H, Shimakawa A, McKenzie C A, Brodsky E, Brittain J H, Reeder S B. Multi-echo water-fat separation and simultaneous R2* estimation with multi-frequency fat spectrum modeling. Magn Reson Med 2008; 60:1122-1134.
In particular in time critical applications such as abdominal imaging in a single breath hold, two-point methods are preferably used to reduce scan times as much as possible. However, they approximate the fat spectrum by a single, dominant peak and thus in general fail to provide a more efficient fat suppression. Moreover, the quality of the fat suppression depends strongly on the choice of echo times in the image data acquisitions.
The identification of water and fat signals is desirable not only for a correct labeling or displaying of resulting images, but also for a robust separation of water and fat signals, which substantially benefits from a better initialization. However, due to inherent ambiguities between chemical shifts and main field inhomogeneities, this is challenging. For two-point Dixon imaging, an identification of water and fat signals was proposed based on a partially-opposed-phase acquisition (Xiang Q S. Two-point water-fat imaging with partially-opposed-phase (POP) acquisition: an asymmetric Dixon method. Magn Reson Med 2006; 56:572-584), exploiting the leading or lagging phase relationship between the two signals. The identification was restricted to the usually small minority of voxels which contain both water and fat, though.
For multi-point Dixon imaging, an identification of water and fat signals was suggested based on a comparison of the residuum remaining with single- and multi-peak spectral models of fat in the separation (Yu H, Shimakawa A, Brittain J H, McKenzie C A, Reeder S B. Exploiting the spectral complexity of fat for robust multi-point water-fat separation. Proc ISMRM 2010; 771). However, this approach is only robust for a higher number of points.